Are You Truly Green? The Impact of Self-Quantification on the Sincerity of Consumers’ Green Behaviors and Sustained Willingness

Abstract

Consumers are increasingly engaging in green consumption practices through the lens of self-quantification. Both the pursuit of positive green data outcomes at the individual level and the comparison and even competition among green data at the community level may lead to insincere green behaviors such as “performative green engagement” beyond the positive outcomes of tracking and measuring one’s green consumption. Compared to outcome-oriented studies exploring the impact of self-quantification on the outcomes of consumers’ green behaviors, this research focuses on the deeper sincerity of behaviors beyond outcomes, comprehensively analyzing the influence of self-quantification on the sincerity of consumers’ green behaviors and their sustained willingness for green consumption. The scenario-based experimental results confirmed that under low situational involvement, in promoting goal-oriented green consumption, self-quantification leads consumers to participate less in substantive environmental activities, with weaker internal motivation, lower sincerity, and weaker sustained willingness for green behaviors. In defensive goal-oriented green consumption, self-quantification encourages consumers to engage more in necessary energy-consuming activities, with stronger internal motivation, higher sincerity, and stronger sustained willingness for green behaviors. Under high situational involvement, consumers with mechanisms for self-quantification and those without exhibit similar levels of green behavior sincerity, with no significant difference in sustained willingness. The findings provide guidance for stakeholders in green consumption to more scientifically quantify the self, promoting proactive and sincere approaches to achieve the sustainable and healthy development of green consumption.

1. Introduction

The rapid advancement of network information technology, the proliferation of innovative mobile smart terminals, the widespread application of portable sensing devices, and the diverse array of instant monitoring online platforms and network communities have led to the integration of a multitude of digital, data-driven, visual, and traceable elements into consumers’ daily consumption practices [1]. Tools like the “Carbon Emission Calculator” for calculating carbon footprints and platforms like “Ant Forest” for recording green energy values have permeated green consumption scenarios, increasingly embedding consumers into data-driven green consumption practices, whether actively or passively [2]. Consumers are increasingly relying on technological tools to track and measure data related to their green behavioral activities, using these quantified data to reflect upon and regulate their participation in green consumption—a phenomenon known as self-quantification. The sharing and comparison of green quantified data within network communities, visible to others, further imbue individual green behaviors with collective characteristics [3]. In the past, some companies occasionally resorted to “greenwashing” tactics to launch green products, aiming to enhance the corporate reputation and conform to social norms [4]. Today, the pursuit of positive green data outcomes at the individual level and the comparison or even competition among green data at the community level may lead to “performative green engagement” or “pseudo-green” behaviors among consumers [5]. Consumers may engage in green consumption through perfunctory or task-oriented approaches, potentially leading to insincere green behaviors. For instance, on the “Ant Forest” platform (an online platform that quantifies users’ green behaviors into “green energy value” to motivate environmental engagement, whose core mechanism leverages the real-time feedback of energy accumulation and gamification design to lower barriers to green participation and foster sustainable lifestyle habits among users), some users may collect green energy from friends rather than through genuine green environmental actions, thereby superficially packaging themselves with quantified data to craft a green image within the community [6]. Why and under what circumstances might the widely applied self-quantification method, intended to positively guide consumer green behaviors, backfire, resulting in insincere green behaviors among consumers?

Existing research generally agrees that, as an effective feedback mechanism, self-quantification enables consumers to rationally regulate their behaviors in green activities, reducing non-green and environmentally unfriendly choices and enhancing green and healthy behavioral outcomes [7]. However, a minority of scholars, based on phenomenological descriptions, have pointed out that through self-quantification, the regulation of consumer behaviors towards green outcomes under data surveillance is not always positive [8]. Furthermore, green consumption is not a short-term behavior that can be achieved overnight while pursuing short-term positive outcomes; it requires sincere, proactive, and long-term continuous participation from consumers [9]. The sustained engagement in green consumption not only requires motivation driven by internal values but also necessitates overcoming the strong inertia of existing non-green consumption habits. The relative insufficiency of internal motivation may lead consumers to seek speculative strategies to maintain surface-level green compliance. This could result in formal participation in low-cost green activities rather than substantive changes to daily behavior, leading to insincere “performative green engagement” [10]. Compared to merely discussing the impact of self-quantification on consumer green behavior outcomes from an outcome-oriented perspective, a deeper analysis of whether consumers under different contextual conditions can actively, sincerely, and continuously participate in green consumption through self-quantification holds more profound significance [11].

Green consumption is often goal-oriented, with consumer green behaviors being actions that align with the principles of sustainable development, based on a profound understanding and recognition of activities that balance environmental protection, emission reduction, energy conservation, and consumption reduction—activities that embody both “destruction and construction”. Exploring the process of change in consumer green behavior preferences and intentions under self-quantification, the type of self-quantification in question should be one that is oriented towards specific goals. Analyzing the impact of self-quantification on consumer green behaviors requires the consideration of goal orientation and activity types [12]. Based on this, by focusing on the deeper sincerity of behaviors beyond just behavioral outcomes, this study will comprehensively analyze the impact of self-quantification on the sincerity of consumers’ green behaviors and their willingness to sustain green practices in different types of green consumption activities under specific goal orientations. The sharing of individual data points within online communities, while promoting the increasingly intergroup nature of self-quantification, also intensifies competition and comparison among individual data points [13]. The application of self-quantification technologies in green consumption not only needs to bring about better green behavioral outcomes in suitable contexts but also must avoid fostering insincere, speculative “performative green engagement” or “pseudo-green” behaviors among consumers who seek advantageous outcomes in community interactions. Clarifying the intrinsic mechanisms and effect boundaries of how self-quantification influences the sincerity of consumer green behaviors will guide relevant stakeholders in green consumption to more scientifically quantify the self, achieving the benign and sustainable development of green consumption through proactive and sincere means.

2. Theoretical Background

2.1. Self-Quantification and Green Consumption

Self-quantification refers to the process of tracking and measuring data related to one’s behavioral activities through technological tools or other recording methods, thereby generating self-knowledge and reflection for intervening in and regulating participation in activities and behavioral decision-making [12]. Self-quantification differs from traditional external feedback and self-monitoring concepts, with its uniqueness manifested in the following: firstly, it provides personalized feedback through technology-enabled self-tracking, offering more targeted insights than non-personalized external feedback [14]; secondly, it delivers standardized feedback through objective data measurement, avoiding the subjective biases inherent in self-monitoring [15]; thirdly, it integrates the complete process of data collection, analysis, and behavioral intervention, emphasizing self-knowledge construction based on data [16]; and most importantly, in the mobile internet era, self-quantification exhibits distinctive community characteristics, where individual data are shared and compared within social groups, creating mechanisms for social interaction and competition [3,6]. This complexity gives self-quantification special value in green consumption research, particularly in terms of its differential impact on different goal-oriented green behaviors, highlighting its theoretical significance.

In the realm of green consumption, self-quantification, as an emerging technological approach, tracks and measures consumers’ green behavioral activities, such as carbon emissions, water usage, and electricity consumption, providing consumers with specific feedback and data support for their green behaviors. This data-driven feedback not only transforms the way consumers perceive their green behaviors but also influences their behavioral choices in green consumption [17]. Tracking and measurement technologies are believed to ensure the digitization of individuals’ green activities, making previously inaccessible green behavioral data at the individual consumer level readily available. This shift offers superior technical accuracy and objectivity compared to subjective speculation about individual behavioral activities, actively reshaping consumers’ inherent resource allocation and decision-making patterns in green consumption [18].

However, compared to other consumption patterns, consumers in green consumption often exhibit a stronger goal orientation [19]. As green consumption involves both “destruction and construction”, the green activities tracked and measured by self-quantification may include relatively positive, promoting goal-oriented behaviors that consumers are encouraged to adopt, such as emission reduction, as well as relatively negative, defensive goal-oriented behaviors that consumers are urged to avoid, such as energy consumption [12]. In recent years, some scholars have found that in green consumption, which encompasses both “destruction and construction”, the effects of self-quantification are not always positive under specific contextual conditions due to differences in goal orientation [18]. The behavioral preferences of consumers after engaging in self-quantification are not always conducive to green outcomes. After tracking and measuring their green activities, consumers may exhibit undesirable participation outcomes and negative regulatory behavioral preferences, potentially reducing the willingness of previously environmentally enthusiastic consumers to continue their eco-friendly practices and causing those who previously limited resource waste to become more extravagant [20]. Many consumers who track and measure their green behaviors tend to abandon both self-quantification and green consumption after short-term participation [2,21]. Under different goal orientations, self-quantification does not always lead to positive green behavioral preferences or sustained green willingness among consumers.

2.2. Sincerity of Green Behaviors

In the field of green consumption, the sincerity of consumers’ behavioral choices is a crucial concept. This refers to whether consumers engage in green consumption out of genuine environmental awareness and green needs, rather than as a perfunctory task, for ostentation, to follow trends, or for other insincere motives [22]. Specifically, sincerity is reflected in whether consumers truly understand the significance of green consumption, whether they genuinely adopt behaviors beneficial to the environment, and whether these behaviors are consistently and stably integrated into their daily lives. The sincerity of consumers’ green behavioral choices determines whether they can wholeheartedly and authentically participate in green consumption [23]. However, in reality, there are instances of insincere performative green engagement or pseudo-green behaviors among consumers. For example, consumers may selectively choose green product categories, using labels such as “green organic” or “zero emissions” as signals to thoughtlessly purchase so-called “green products”. In reality, these products may not meet environmental standards, or these consumption behaviors may not genuinely reduce adverse environmental impacts [24]. Furthermore, with the emergence of green data tracking and sharing network communities such as “Ant Forest”, some consumers, in pursuit of fashion or social recognition, blindly chase numerical green metrics by collecting friends’ “green energy values”. While they may rank high in “green energy values” within the network community, they do not genuinely fulfill green behaviors, participating in green consumption activities with a speculative mindset [6]. Such insincere green behaviors may reduce green practices to mere formalities, and the lack of sincerity in consumers’ initial commitment to green participation may ultimately undermine their motivation to sustain green practices [25].

3. Research Model and Hypotheses

The internal mechanism through which self-quantification influences the sincerity of consumers’ green behaviors under different goal orientations in green consumption, thereby affecting their willingness to sustain green consumption, is illustrated in Figure 1.

In promoting goal-oriented green consumption, self-quantification technologies (such as online platforms that record green energy values or applications that track emission reductions) provide consumers with immediate feedback on their promoting goal-oriented green consumption behaviors. These technologies were originally designed to incentivize consumers to participate more actively in promoting goal-oriented green activities, such as reducing carbon emissions, through data-driven approaches. However, in practice, self-quantification may, to some extent, diminish the arousal of consumers’ internal motivation, thereby affecting the sincerity of their behavioral choices [26]. Internal motivation refers to the drive that leads consumers to act based on personal interests or values or intrinsic satisfaction [27], such as the satisfaction of feeling proud after reducing carbon emissions. In contrast, the immediate pleasure derived from gamified elements in green activities, such as point collection, represents external motivation [13]. Particularly in community contexts, when quantified data are directly linked to external incentives like points, or community rankings, this may strengthen external motivation, causing consumers to overly focus on achieving metrics rather than the environmental essence [28]. In the context of self-quantification, consumers may become overly focused on achieving specific quantified metrics, such as green energy values or rankings, while neglecting the essence and long-term significance of green behaviors. This overemphasis on external incentives may weaken consumers’ inherent interest and enthusiasm for green living, leading them to engage in insincere behaviors, such as cheating or exaggerating, to achieve better data performance [29]. In community settings, individual consumers are often influenced by peer pressure or incentives to pursue green goals. However, when faced with promoting goal-oriented green consumption activities that offer potential gains but lack intrinsic appeal, individual consumers may remain inactive, as their participation is more likely driven by internal motivations rooted in personal interests and needs [30]. Nevertheless, self-quantification can also serve as an external incentive. Compared to general external incentives, this form of incentive, which relies on data about individual consumers’ behavioral states and community comparisons, may lead consumers to prioritize superficial quantified achievements over the essence of green behaviors. For example, in the “Ant Forest” online community, consumers might collect large amounts of green energy values from friends to achieve higher rankings. Such behavior is not driven by genuine concern for environmental protection but rather by the desire for better rankings and recognition within the community [31]. As Hu et al. stated, consumers will participate in green consumption activities opportunistically rather than sincerely [6]. This outcome-oriented behavioral pattern not only undermines the internal motivation for environmental promotion and green improvement in consumers’ participation in green activities but may also lead to phenomena such as “performative green engagement” and “pseudo-green” behaviors. The quantified data obtained through self-quantification may become the sole criterion for consumer behavior, while the true value of green practices is overlooked or marginalized [16]. In communities focused on promoting goal-oriented green consumption, self-quantification may exacerbate the “performative green engagement” and “pseudo-green” phenomena. Self-quantification can undermine the arousal of consumers’ intrinsic motivation, indirectly leading them to rely more on fabricating data or employing other insincere means to enhance the quantifiable metrics of pro-environmental behavior (e.g., green points, rankings). This, in turn, allows them to project a positive green image within their community [15,16].

H1a. 

Under promoting goal orientation, compared to non-self-quantification, self-quantification will reduce the sincerity of consumers’ green behaviors.

H1b. 

The arousal of consumers’ internal motivation mediates the effects of self-quantification on the sincerity of their green behaviors under promoting goal orientation.

As Gao and Zhang pointed out, green consumption involves both “destruction and construction”, with both promoting goal-oriented behaviors and defensive goal-oriented behaviors [17]. In contrast, in the context of defensive goal-oriented green consumption, self-quantification may enhance the sincerity of consumers’ green behavior choices by fostering their internal motivation. Defensive goal-oriented green consumption typically involves reducing adverse environmental impacts, such as conserving water and electricity. Under external norms like social energy-saving directives and group energy reduction ideologies, individual consumers often engage in controlling water and electricity usage more due to external pressures rather than internal motivations such as personal interest or awareness. Consumers inherently desire and yearn for an unconstrained lifestyle [32,33]. However, external motivations are generally less effective than internal ones, leading to inaction or even opportunistic behavior preferences among consumers in defensive goal-oriented green consumption, especially in ambiguous situations where they may not realize the negative impacts of their actions [34]. In the context of self-quantification, however, the presentation of and reminders given by quantified data on energy use activities that were previously difficult to observe or be aware of make individual consumers realize the excessiveness of their defensive goal-oriented participation and the ease with which negative impacts are caused, especially after seeing their own and others’ water and electricity usage data within the community [12]. In defensive goal-oriented green consumption, self-quantification provides consumers with direct and objective feedback on the adverse environmental impacts of their behavior compared to others in the community [18]. This feedback not only helps consumers become aware of the potential harm of their previously unnoticed behaviors but also stimulates internal motivations such as saving face and reducing negative impacts [35]. For example, when residents learn through smart meters that their previously unnoticed electricity usage and increases exceed the average level of their community neighbors, it makes them realize the necessity of controlling their electricity usage, thereby leading them to actively rather than passively adjust their electricity habits, choose more energy-efficient appliances, or reduce unnecessary electricity activities, striving to genuinely lower their electricity usage levels in the community [36].

H2a. 

Under defensive goal orientation, compared to non-self-quantification, self-quantification will enhance the sincerity of consumers’ green behavior.

H2b. 

The arousal of consumers’ internal motivation plays a mediating role in the impact of self-quantification on the sincerity of their green behaviors under defensive goal orientation.

The degree of situational involvement of consumers in green consumption may vary, which in turn influences the arousal of their motivation to participate in green consumption. Situational involvement refers to the extent to which individual consumers perceive the importance of green issues and their relevance to themselves [37]. Consumers with high situational involvement perceive green issues as highly important, closely related to themselves; possess substantial green knowledge; and exhibit heightened attention and vigilance toward green issues, believing that their actions can effectively influence the green context. Taking pro-environmental consumption as an example, Bhate’s (2002) research indicates that consumers with high situational involvement are more likely to engage in recycling and green donation activities and adopt pro-environmental behaviors, demonstrating an intrinsic need and motivation to enhance participation in promoting goal-oriented pro-environmental consumption that benefits environmental protection [38]. Conversely, consumers with low situational involvement often lack situational knowledge and interest, as well as internal motivation to pay attention to the situational attributes of green activities [39]. They exhibit weaker internal motivation to focus on situational information and rely more on visually compelling and persuasive situational information (such as quantified data on green activities like green energy values), adjusting their attitudes and related decision-making behaviors based on external motivations driven by intuitive information [40].

Based on the hierarchical model of motivation [41], the impact of green consumption contexts on behavioral sincerity must operate through a sequential mediation pathway (motivation to behavior causal chain). Situational involvement modulates the perceived salience of goal values (e.g., self-relevance of environmental issues) [42], directly influencing motivational intensity rather than bypassing the mediating mechanism to affect behavioral outcomes. According to the internalization mechanism of self-determination theory, under high situational involvement, individuals internalize environmental goals in their self-identity through integrated regulation (autonomous motivation), where external incentives from self-quantification (e.g., energy value) conflict with intrinsic needs and fail to substitute the intrinsic drivers of sincerity [15]. Conversely, under low involvement, external quantified feedback operates via external regulation as the dominant motivational source, yet its association with sincere behavior is constrained by the instrumental nature of goals (i.e., pursuing data rewards rather than genuine environmental commitment) [10,26]. The presentation and highlighting of behavioral state data related to green consumption by self-quantification may have differential impacts on consumers with varying degrees of situational involvement. High-situational-involvement consumers who receive quantified data are likely to further explore other aspects of green consumption information, driven by stronger internal motivation for information processing. In contrast, low-situational-involvement consumers who receive quantified data lack the internal motivation to explore additional green consumption information and instead respond behaviorally under external motivation, relying on intuitive and more persuasive quantified data [43].

H3. 

The degree of situational involvement in green activities moderates the impact of self-quantification on the arousal of consumers’ internal motivation under different goal orientations.

The sincerity of green behavior reflects the genuine willingness of consumers to participate in green consumption. When consumers spontaneously choose green products and services without external pressure or vanity, their actions are based on an identification with green environmental protection and personal values. This internal motivation prompts them to pay more sincere attention to the environmental attributes, green benefits, and alignment with their lifestyle of products during consumption, truly understanding and recognizing the importance of green consumption [44]. As scholars have pointed out, this sincere understanding and recognition of green consumption can truly enable consumers to continue participating in green consumption, rather than turning green consumption into a formality and giving up on participating in both self-quantification and green consumption after short-term participation [21,23,25]. Consequently, they are more willing to engage in green consumption continuously, as this consumption mode aligns with their genuine needs and long-term interests [45]. Compared to insincere green behaviors such as pseudo-green and performative green engagement, consumers’ sincere green behaviors often lead to more positive psychological experiences. Performative green engagement and pseudo-green behaviors are often accompanied by deception and disguise, which not only harm consumers’ self-identity and inner peace but may also trigger a crisis of community trust. In contrast, sincere green behaviors allow consumers to feel that their efforts and contributions have yielded real returns, such as improved health and environmental benefits. This positive psychological experience further motivates them to continue participating in green consumption [46].

H4. 

The sincerity of consumers’ green behavior will positively influence their sustained willingness for green consumption.

To validate the hypotheses, this study employed scenario-based simulation experimental designs to systematically examine the impact of self-quantification on the sincerity of consumers’ green behaviors and sustained willingness. Through randomized group assignments manipulating self-quantification technologies (e.g., energy value feedback) and goal orientations (promoting goal-oriented environmental protection activities vs. defensive goal-oriented energy-saving activities), combined with pre-validated classifications of substantive/non-substantive and necessary/unnecessary behaviors, participants’ internal motivation arousal, behavioral sincerity (indicated by proportions of substantive or necessary behaviors), and sustained willingness were measured. The experimental design controlled for confounding variables such as initial preference and perceived difficulty, utilizing bootstrap mediating effect testing and moderating effect analysis to systematically reveal the differentiated pathways through which self-quantification operates across distinct contextual scenarios.

4. Pilot Experiment

4.1. Interview Design

Drawing on the paradigm of Sheng et al. (2019) [43], this study referenced China’s large-scale promoting goal-oriented green online community, “Ant Forest” (which tracked and recorded individual green behaviors, converted them into green energy values, and presented and compared these values within the community). The platform’s current task categories that generated green energy values were systematically reviewed. A total of 4 experts in the field of green consumption and 16 members of environmental protection organizations were invited to classify these green energy value-generating tasks into substantive and non-substantive behaviors based on their environmental impact. These tasks were then evaluated according to the criteria of substantiveness and non-substantiveness. Substantiveness refers to the attribute of an action that can directly and effectively generate real environmental benefits, reflecting the direct causal relationship between the action and environmental improvement. Non-substantiveness refers to actions that primarily express environmental attitudes in form or appearance but lack actual environmental contributions. Substantive green behaviors refer to actions that genuinely and significantly enhance environmental performance, such as recycling and other environmental measures taken to achieve green goals. In contrast, non-substantive green behaviors refer to actions that help individuals establish or maintain an environmental image but do not truly contribute to green benefits, such as participating in environmental advocacy campaigns or praising others’ environmental actions [47].

Drawing on the paradigm of Zhang et al. (2024) [12], this study focused on the daily energy consumption scenarios of university students, such as water and electricity usage, and systematically reviewed the categories of activities that potentially consume energy in their daily lives. A total of 4 experts in the field of green consumption and 16 members of environmental protection organizations were invited to classify these daily energy consumption activities into necessary and unnecessary behaviors based on their essentiality. These activities were then evaluated according to the criteria of necessity and non-necessity. Necessity refers to the attribute of energy consumption that is indispensable for meeting basic needs in daily life. Non-necessity refers to energy consumption that can be replaced or reduced, primarily serving convenience and comfort rather than basic survival needs. Necessary energy consumption activities refer to those that are essential for meeting basic living needs, such as charging a mobile phone. In contrast, non-necessary energy consumption activities refer to those that are not essential for meeting basic living needs but can enhance the quality of life or convenience, such as using air conditioning [48].

4.2. Interview Results

According to the evaluation results of the interview, among the 16 categories of green energy value-generating tasks, the 8 tasks with relatively higher scores in terms of substantiveness included walking, taking public transportation, shared biking, using green packaging, recycling old clothes, recycling old books, dining without disposable utensils, and plastic reduction. The 8 tasks with relatively higher scores in terms of non-substantiveness included online payments, utility bill payments, liking friends’ green updates, collecting friends’ energy, watering interactions, planting a tree together, learning green lifestyle tips, and playing the energy rain mini-game. Among the 16 categories of daily energy consumption activities, the 8 activities with relatively higher scores in terms of necessity included brushing one’s teeth and washing one’s face, flushing the toilet, charging a mobile phone, using a computer, using fluorescent lights, washing one’s hands and fruits, taking a shower, and handwashing clothes. The 8 activities with relatively higher scores in terms of non-necessity included using a fan, using a hair dryer, using air conditioning, using a washing machine, traveling by electric bike, mopping the floor, using an electric mosquito repellent, and watering plants.

4.3. Design of Pilot Experiment

A total of 80 undergraduate students (52.500% male) were recruited from a university in Jiangxi Province, and all participants were randomly and equally divided into four groups: A, B, C, and D. Among these experimental groups, participants in Groups A and B were assigned to promoting goal-oriented green consumption scenarios, while participants in Groups C and D were exposed to defensive goal-oriented green consumption scenarios. Participants in Groups A and B were provided with an explanation of what constitutes substantive and non-substantive pro-environmental behaviors related to sincerity. Participants in Groups C and D were provided with an explanation of what constitutes necessary and non-necessary energy consumption behaviors related to sincerity.

Subsequently, participants in Group A were asked to read the following: “There is an online platform where you can earn green energy by participating in activities to promote environmental protection. Specific activities include walking, taking public transportation, shared biking, using green packaging, recycling old clothes, recycling old books, dining without disposable utensils, and plastic reduction”. Participants in Group B were asked to read the following: “There is an online platform where you can earn green energy by participating in activities to promote environmental protection. Specific activities include online payments, utility bill payments, liking friends’ green updates, collecting friends’ energy, watering interactions, planting a tree together, learning green lifestyle tips, and playing the energy rain mini-game”. After reading these materials, participants were asked to rate individual pro-environmental behaviors on a semantic differential scale (1 representing non-substantive pro-environmental behavior and 7 representing substantive pro-environmental behavior).

Participants in Group C were asked to read the following: “In daily campus dormitory life, we can reduce our environmental burden by saving energy. Specific energy consumption activities include brushing teeth and washing face, flushing the toilet, charging a mobile phone, using a computer, using fluorescent lights, washing hands and fruits, taking a shower, and hand-washing clothes”. Participants in Group D were asked to read the following: “In daily campus dormitory life, we can reduce our environmental burden by saving energy. Specific energy consumption activities include using a fan, using a hair dryer, using air conditioning, using a washing machine, traveling by electric bike, mopping the floor, using electric mosquito repellent, and watering plants”. After reading these materials, participants were asked to rate individual energy consumption behaviors on a semantic differential scale (1 representing non-necessary energy consumption behavior and 7 representing necessary energy consumption behavior).

4.4. Results of of Pilot Experiment

The results showed that the ratings in Group A were significantly higher than those in Group B (M = 6.600 vs. M = 1.450, t(38) = 27.074, p < 0.001), and the mean ratings of both groups were far from the midpoint of 4. This indicated that the manipulation of the substantive nature of individual pro-environmental behaviors in the pilot experiment was successful and could be used in the main experiment.

The results showed that the ratings in Group C were significantly higher than those in Group D (M = 6.500 vs. M = 1.900, t(38) = 21.877, p < 0.001), and the mean ratings of both groups were far from the midpoint of 4. This indicated that the manipulation of the necessity of individual energy consumption behaviors in the pilot experiment was successful and could be used in the main experiment.

Promoting goal orientation and defensive goal orientation have essential differences in green consumption activities. Promoting goals involve proactive behaviors like reducing carbon emissions or increasing green energy values, while defensive goals focus on avoiding negative actions such as controlling water and electricity usage. These differences extend to the types of activities and data collection methods used in real-life scenarios. Integrating both goal orientations into a single experiment could complicate the design, affecting operability and result clarity. Therefore, in formal experiments, we chose the “Ant Forest” platform for the promoting goal experiment, as it records and rewards promoting goal-oriented green behaviors, and a daily energy use scenario for university students for the defensive goal experiment, as it can be used to record and provide feedback on defensive goal-oriented green behaviors. These choices were based on their typicality and representativeness for their respective goal orientations. Moreover, the hypotheses tested in the two experiments are conceptually unified. Both explore how self-quantification influences consumers’ internal motivation, thereby affecting the sincerity and continuity of green behaviors.

5. Experiment 1: Promoting Goal-Oriented Green Energy Value Tracking

5.1. Design of Experiment 1

A total of 120 students from a university in Jiangxi Province were recruited to participate in an environmental protection activity during a weekend in October 2024 (mean age = 19.792 years, 45.833% male). The participants were randomly divided into Group A and Group B. Prior to the experiment, participants were informed about the following: “There is an online platform that records individual environmental protection behaviors. You can use this platform to log different environmental actions and earn green energy. The more green energy value you accumulate, the more environmentally friendly you are considered”. At the beginning of the experiment, the researchers provided the participants with a list of 16 subcategories of environmental activities, divided into two major categories: substantive and non-substantive. This list included the value of green energy that could be earned for completing each type of activity once (refer to

Table 1. List of environmental activity categories.

Activity Name	Green Energy Value per Instance	Activity Name	Green Energy Value per Instance
Walking 5000 steps	5 g	Using online payment for shopping once	5 g
Using shared bike rides once	5 g	Using online utility payment once	5 g
Taking public transportation once	5 g	Liking one user’s green profile	5 g
Dining without disposable utensils once	5 g	Learning one green living tip	5 g
Recycling one plastic bottle	10 g	Playing the energy rain mini-game once	10 g
Recycling one packaging box	10 g	Collecting energy from one user	10 g
Recycling one old book	15 g	Watering one user’s virtual tree	15 g
Recycling one piece of old clothing	30 g	Co-planting a virtual tree with one user	30 g

for details). After reviewing the list, participants were instructed as follows: “Please take advantage of this weekend to engage in environmental activities as much as you like and record your green behaviors on the platform”.

Next, participants were required to scan a QR code with their smartphones to access a mini-program. The mini-program included four sections: “Environmental Knowledge”, “Environmental Games”, “Environmental Leaders”, and “Environmental Actions”. Clicking on “Environmental Knowledge” would display a tip related to eco-friendly living. Clicking on “Environmental Games” would lead to an energy rain game where energy drops could be collected. Clicking on “Environmental Leaders” would show 12 virtual platform users, and clicking on a user’s avatar would take the participant to the user’s profile page, which displayed a virtual tree belonging to that user. Below the tree were buttons labeled “Like”, “Water”, “Co-plant”, and “Collect”. Upon first clicking “Environmental Actions”, the mini-program interface would again display the 16 different environmental activity labels and prompt the participants with the following: “You will decide which activities to participate in over the next 48 h. After completing each activity, return to the mini-program and click the corresponding activity label to earn green energy. Each activity label can be clicked repeatedly to log multiple instances, and green energy value will accumulate accordingly. Each activity can be repeated up to 12 times (except for using online payment for shopping)”.

Participants were informed that the purpose of the activity was to test the design experience of the mini-program. They were also told that they would need to answer several questions after the activity concluded. The value of green energy accumulated and the number of activity categories chosen would not affect their experimental compensation. However, participants were required to truthfully complete the environmental activities they selected, and their participation would be verified before they received their compensation. The mini-program’s backend recorded the following data for each participant over the 48 h period: which environmental activity categories they chose to participate in, the number of times they participated in each category, the total value of green energy accumulated, and the proportion of substantive environmental activities out of the total number of activities participated in.

In the non-self-quantification condition, each time participants entered the mini-program and clicked on the label of a completed activity, a prompt appeared at the top of the interface stating, “You have completed X environmental activity”. In the self-quantification condition, each time participants entered the mini-program and clicked on the label of a completed activity, a prompt appeared at the top of the interface stating, “You have earned a total of Xg green energy”. After the activity participation concluded, participants were required to report their level of internal motivation arousal during the activity through the mini-program. The level of internal motivation arousal was measured using a 3-item, 5-point Likert scale. Specific items included the following: participating in environmental activities out of personal interest rather than external stimuli, out of personal values rather than external stimuli, and out of a sense of inner fulfillment rather than external stimuli [49]. Additionally, participants reported their sustained willingness to participate in similar environmental activities in the future. Specific items included the following: if given the opportunity, you would participate in similar activities again; you can foresee yourself participating in similar activities again; and you would consider continuing to participate in similar activities in the future [50].

Regarding the measurement of situational involvement, to prevent experimental material information from interfering with participants’ responses, participants were asked to complete a 5-point Likert scale questionnaire on situational involvement before the experiment began. Specific items included the following: you believe environmental protection is important; environmental issues are closely related to your life; you have a high level of concern for environmental issues; and your environmental behaviors impact the environment [51]. Responses ranged from 1 = strongly disagree to 5 = strongly agree. To assess the sincerity of participants’ green behaviors, the proportion of substantive environmental activities participated in relative to the total number of activities was measured, thereby evaluating the sincerity of their behavior during the activity participation process. Considering that related factors might interfere with participants’ activity category choices [52], participants also reported their initial level of preference for the activities (“How much did you like environmental activities before participating in this activity?” 1 = strongly dislike; 5 = strongly like) and perceived difficulty (“Participating in this activity was difficult for you”, 1 = strongly disagree; 5 = strongly agree). Subsequently, demographic information on the participants was recorded.

5.2. Results of Experiment 1

The reported levels of preference for environmental activities (F(3, 116) = 0.058, p = 0.982) and perceived difficulty (F(3, 116) = 0.137, p = 0.938) showed no significant differences across the groups, thereby ruling out the interference of these factors on the sincerity of participants’ engagement in environmental activities. Regarding the arousal of internal motivation, the Cronbach’s α value for the measurement items was 0.944. The independent sample t-test results indicated that participants in the self-quantification condition exhibited weaker internal motivation arousal compared to those in the non-self-quantification condition (M = 3.178 vs. M = 3.694, t(118) = −2.990, p = 0.003). Participants in the self-quantification condition also had a lower proportion of substantive environmental activities relative to their total participation (M = 29.443% vs. M = 36.484%) compared to the non-self-quantification group (t(118) = −3.695, p < 0.001). In terms of sustained willingness for participation, the Cronbach’s α value for the measurement items was 0.944. Participants in the self-quantification condition had an average green energy value of 710.417 g, which was significantly higher than the 458.583g for participants in the non-self-quantification condition (M = 6.516 vs. M = 6.095, t(118) = 7.780, p < 0.001, data were log-transformed). However, participants in the self-quantification condition exhibited lower sustained willingness for participation compared to those in the non-self-quantification condition (M = 3.289 vs. M = 3.817, t(118) = −3.010, p < 0.001) (refer to Figure 2 for details). The regression analysis results revealed that the arousal of internal motivation positively influenced the proportion of substantive environmental activities (β = 0.108, t(118) = 38.715, p < 0.001), which in turn positively affected the sustained willingness for participation (β = 8.576, t(118) = 32.569, p < 0.001). Hypotheses H1a and H4 were supported.

Following the analytical procedure outlined by Zhao et al. (2010) [53], the bootstrap mediating effect test method recommended by Preacher et al. (2007) [54] was employed to examine the mediating effects of internal motivation arousal. Model 4 was selected, with the sample size set to 5000, and the bias-corrected nonparametric percentile sampling method was used to test the mediating effects. The bootstrap analysis results confirmed that in the context of promoting goal-oriented green consumption, the impact of self-quantification on consumers’ sincerity in green behaviors was mediated by the level of internal motivation arousal. The indirect effects of self-quantification were significant (mean bootstrap estimate = −0.055, SE = 0.018; 95% CI = −0.089, −0.019, excluding 0). Hypothesis H1b was supported. To examine the sequential mediation effects of internal motivation arousal and sincerity in green behaviors, Model 6 was selected. The bootstrap analysis results confirmed that in the context of promoting goal-oriented green consumption, self-quantification influenced consumers’ internal motivation arousal, which in turn affected their behavioral sincerity in green behaviors, ultimately influencing their sustained willingness for participation. The indirect effects of self-quantification were significant (mean bootstrap estimate = −0.515, SE = 0.176; 95% CI = −0.864, −0.182, excluding 0).

The moderating effects of situational involvement were tested. The Cronbach’s α value for the situational involvement measurement items was 0.953. Since situational involvement was measured as a continuous variable, participants in Group A and Group B were divided into high and low groups based on the mean ± 1 standard deviation (SD), respectively. This division allowed for the analysis of the moderating role of situational involvement in the effects of self-quantification on consumers’ internal motivation arousal. Using the bootstrap method, Model 1 was selected for data analysis. The results indicated that the interaction effect between self-quantification and situational involvement on internal motivation arousal was significant (β = 0.811, t(118) = 3.142, p = 0.002). In the low-situational-involvement group, compared to the non-self-quantification condition, consumers in the self-quantification condition exhibited weaker internal motivation arousal (M = 2.378 vs. M = 3.300, t(58) = −4.546, p < 0.001), a lower proportion of substantive environmental activities (M = 19.269% vs. M = 32.935%, t(58) = −6.860, p < 0.001), and weaker sustained willingness for participation (M = 2.467 vs. M = 3.456, t(58) = −4.830, p < 0.001). In contrast, in the high-situational-involvement group, there were no significant differences in internal motivation arousal between the self-quantification and non-self-quantification conditions (M = 3.978 vs. M = 4.089, t(58) = −0.696, p = 0.489) nor in the proportion of substantive environmental activities (M = 39.617% vs. M = 40.033%, t(58) = −0.248, p = 0.805) or sustained willingness for participation (M = 4.111 vs. M = 4.178, t(58) = −0.401, p = 0.690) (refer to Figure 3 and

Table 2. The results of Experiment 1 under different levels of situational involvement.

Situational Involvement	Variable	Condition	Mean	Standard Deviation	T	95% Confidence Interval
						LLCI	ULCI
Low Situational Involvement	Substantive Proportion	Non-Self-Quantification Self-Quantification	0.329 0.193	0.091 0.061	6.860	0.097	0.177
	Green Energy	Non-Self-Quantification Self-Quantification	414.000 829.333	112.045 166.680	−11.327	−488.732	−341.934
	Logarithm of Green Energy	Non-Self-Quantification Self-Quantification	5.988 6.699	0.286 0.216	−10.877	−0.842	−0.580
	Internal Motivation Arousal	Non-Self-Quantification Self-Quantification	3.300 2.378	0.837 0.731	4.546	0.516	1.328
	Sustained Willingness	Non-Self-Quantification Self-Quantification	3.456 2.467	0.780 0.805	4.830	0.579	1.399
High Situational Involvement	Substantive Proportion	Non-Self-Quantification Self-Quantification	0.400 0.396	0.069 0.060	0.248	−0.029	0.038
	Green Energy	Non-Self-Quantification Self-Quantification	503.167 591.500	99.987 196.417	−2.195	−168.882	−7.785
	Logarithm of Green Energy	Non-Self-Quantification Self-Quantification	6.202 6.334	0.195 0.314	−1.944	−0.266	0.004
	Internal Motivation Arousal	Non-Self-Quantification Self-Quantification	4.089 3.978	0.625 0.612	0.696	−0.209	0.431
	Sustained Willingness	Non-Self-Quantification Self-Quantification	4.178 4.111	0.630 0.657	0.401	−0.266	0.399

for details). Hypothesis H3 was supported.

6. Experiment 2: Defensive Goal-Oriented Energy Consumption Tracking

6.1. Design of Experiment 2

A total of 120 students (mean age = 20.017 years, 50.833% male) from a university in Jiangxi Province were recruited to participate in an energy-saving activity on a Tuesday in October 2024 (a day without classes). The participants were randomly divided into Group A and Group B. Before the experiment began, participants were informed about the following: “There is currently an online platform that records individual energy usage behaviors. You can use this platform to record different energy usage behaviors and mark energy consumption values. Accumulating more energy consumption values means you are using more energy”. At the start of the experiment, the experimenters presented the participants with a list of 16 subcategories of energy usage activities, divided into two major categories (necessary and unnecessary). This list included the energy consumption value marked for each single execution of the activity (the details of the categories are shown in

Table 3. List of energy usage activity categories.

Activity Name	Energy Consumption per Instance	Activity Name	Energy Consumption per Instance
Brushing one’s teeth and washing one’s face once	5 g	Watering one pot of plants	5 g
Washing one’s hands or fruits once	5 g	Using electric mosquito repellent liquid for 2 h	5 g
Charging a mobile phone once	10 g	Using an electric fan for 2 h	10 g
Using fluorescent lights for 2 h	10 g	Using a hair dryer for 10 min	10 g
Using a computer for 2 h	10 g	Riding an electric bike on campus once	10 g
Flushing the toilet once	15 g	Mopping the dormitory floor once	15 g
Handwashing one piece of clothing	15 g	Using a washing machine for 15 min	15 g
Taking a shower for 15 min	30 g	Using air conditioning for 2 h	30 g

). After reviewing the list, participants were instructed as follows: “Please try to control your energy usage activities as much as possible this Tuesday and record your energy usage behaviors on the platform”.

Subsequently, participants were required to scan a QR code with their smartphones to access a mini-program. Upon entering the mini-program, the interface displayed the 16 different energy usage category labels again. Participants were prompted as follows: “You will decide which energy usage activities to perform over the next 24 h. After completing each activity, enter the mini-program and click the corresponding activity label to record the energy consumption value. Each activity label can be clicked repeatedly to accumulate energy consumption values, and each activity can be repeated up to 12 times”. Participants were informed that the purpose of the activity was to test the design experience of the mini-program. They were also told that they would need to answer several questions after the activity. The total energy consumption values recorded, the number of energy usage activities performed, and the types of activities engaged in would not affect their experimental compensation. However, participants were required to truthfully record the types of energy usage activities they performed, and their compensation would only be granted after verification. The mini-program backend recorded the following data for each participant over the 24 h period: the types of energy usage activities performed, the number of times each type of activity was engaged in, the total accumulated energy consumption values, and the proportion of necessary energy usage activities relative to the total number of activities performed.

In the non-self-quantification condition, each time participants entered the mini-program and clicked on the label of an energy usage activity they had performed, a prompt appeared at the top of the interface stating, “You have performed X energy usage activity”. In the self-quantification condition, each time participants entered the mini-program and clicked on the label of an energy usage activity they had performed, a prompt appeared at the top of the interface stating, “You have generated a total of Xg energy consumption value”. After the activity concluded, participants were required to report their level of internal motivation arousal during the activity through the mini-program. The level of internal motivation arousal was measured using a 3-item, 5-point Likert scale. The specific items included the following: controlling energy usage activities out of self-awareness rather than external stimuli, out of personal values rather than external stimuli, and out of a sense of inner fulfillment rather than external stimuli [49]. Additionally, participants reported their sustained willingness to control similar energy usage activities in the future. The specific items included the following: if given the opportunity, you would participate in similar energy control activities again; you could foresee yourself participating in similar energy control activities again; and you would consider continuing to participate in similar energy control activities in the future [50].

Regarding the measurement of situational involvement, to prevent experimental material information from interfering with participants’ responses, participants were asked to complete a 5-point Likert scale questionnaire on situational involvement before the experiment began. The specific items included the following: you believe energy control is important; energy control issues are closely related to your life; you are highly concerned about energy control issues; and your energy control behaviors impact the environment [51]. Responses ranged from 1 = strongly disagree to 5 = strongly agree. To assess the sincerity of participants’ green behaviors, the proportion of necessary energy usage activities relative to the total number of activities performed was measured to evaluate the sincerity of their participation in energy control activities. Considering that related factors might interfere with participants’ choice of activity categories [52], participants also reported their initial level of preference for the activities (“How much did you like energy control activities before participating in this activity?” 1 = strongly dislike; 5 = strongly like) and perceived difficulty (“Participating in this activity was difficult for you”, 1 = strongly disagree; 5 = strongly agree). Subsequently, demographic information on the participants was recorded.

6.2. Results of Experiment 2

No significant differences were observed among the groups in terms of their reported preference for energy control activities (F(3, 116) = 0.794, p = 0.500) or perceived difficulty (F(3, 116) = 1.336, p = 0.266). This ruled out the potential influence of these factors on the sincerity of participants’ engagement in energy control activities. Regarding the arousal of internal motivation, Cronbach’s α for the measurement items was 0.888. Independent sample t-tests revealed that participants in the self-quantification group exhibited significantly higher internal motivation arousal compared to those in the non-self-quantification group (M = 3.633 vs. M = 3.156, t(118) = 3.413, p = 0.001). Participants in the self-quantification condition also had a higher proportion of necessary energy control activities relative to their total participation (M = 72.975% vs. M = 66.488%) compared to the non-self-quantification group (t(118) = 3.746, p < 0.001). In terms of sustained willingness for participation, Cronbach’s α for the measurement items was 0.888. The average energy consumption of participants in the self-quantification group was 286.083 g, significantly lower than that of the non-self-quantification group (337.917 g) (M = 5.644 vs. M = 5.796, t(118) = −4.135, p < 0.001; data were log-transformed). However, participants in the self-quantification group demonstrated a stronger sustained willingness to control their energy consumption compared to the non-self-quantification group (M = 3.761 vs. M = 3.400, t(118) = 2.734, p = 0.007) (refer to Figure 4 for details). The regression analysis results indicated that internal motivation arousal positively influenced the proportion of necessary energy control activities (β = 0.119, t(118) = 33.482, p < 0.001), which in turn positively affected the sustained willingness for controlling energy consumption (β = 6.902, t(118) = 27.136, p < 0.001). Hypotheses H2a and H4 were supported.

Following the analytical procedure outlined by Zhao et al. (2010) [53], the bootstrap mediating effect test method recommended by Preacher et al. (2007) [54] was employed to examine the mediating effects of internal motivation arousal. Model 4 was selected, with the sample size set to 5000, and the bias-corrected nonparametric percentile sampling method was used to test the mediating effects. The bootstrap analysis results confirmed that in the context of defensive goal-oriented green consumption, the impact of self-quantification on consumers’ sincerity in green behavior was mediated by the level of internal motivation arousal. The indirect effects of self-quantification were significant (mean bootstrap estimate = 0.056, SE = 0.016; 95% CI = [0.023, 0.087], excluding 0). Hypothesis H2b was supported. To examine the sequential mediation effects of internal motivation arousal and sincerity in green behaviors, Model 6 was selected. The bootstrap analysis results confirmed that in the context of defensive goal-oriented green consumption, self-quantification influenced consumers’ internal motivation arousal, which in turn affected their behavioral sincerity in green behaviors, ultimately influencing their sustained willingness for participation. The indirect effects of self-quantification were significant (mean bootstrap estimate = 0.443, SE = 0.129; 95% CI = 0.189, 0.692, excluding 0).

The moderating effects of situational involvement were examined. Cronbach’s α for the situational involvement measurement items was 0.951. Since situational involvement was measured as a continuous variable, participants in Group A and Group B were divided into high and low groups based on the mean ± 1 standard deviation (SD), respectively. This division allowed for the analysis of the moderating role of situational involvement in the effects of self-quantification on consumers’ internal motivation arousal. Using the bootstrap method, Model 1 was selected for data analysis. The results indicated that the interaction between self-quantification and situational involvement in terms of internal motivation arousal was significant (β = −0.844, t(118) = −3.366, p = 0.001). Under low situational involvement, consumers exhibited weaker internal motivation arousal in the non-self-quantification condition compared to the self-quantification condition (M = 3.567 vs. M = 2.667, t(58) = 5.440, p < 0.001), a lower proportion of necessary energy control activities (M = 72.036% vs. M = 60.957%, t(58) = 4.925, p < 0.001), and lower sustained willingness for energy control behavior (M = 3.733 vs. M = 2.956, t(58) = 4.658, p < 0.001). In contrast, under high situational involvement, there were no significant differences in internal motivation arousal between the self-quantification and non-self-quantification conditions (M = 3.700 vs. M = 3.644, t(58) = 0.295, p = 0.769), the proportion of necessary energy control activities (M = 73.915% vs. M = 72.019%, t(58) = 0.851, p = 0.399), or sustained willingness for energy control behavior (M = 3.789 vs. M = 3.844, t(58) = −0.324, p = 0.747) (refer to Figure 5 and

Table 4. The results of Experiment 2 under different levels of situational involvement.

Situational Involvement	Variable	Condition	Mean	Standard Deviation	T	95% Confidence Interval
						LLCI	ULCI
Low Situational Involvement	Necessary Proportion	Non-Self-Quantification Self-Quantification	0.610 0.720	0.081 0.093	−4.925	−0.156	−0.066
	Energy Consumption	Non-Self-Quantification Self-Quantification	396.333 300.000	51.744 48.778	7.420	70.345	122.322
	Logarithm of Energy Consumption	Non-Self-Quantification Self-Quantification	5.973 5.691	0.138 0.162	7.272	0.205	0.360
	Internal Motivation Arousal	Non-Self-Quantification Self-Quantification	2.667 3.567	0.594 0.685	−5.440	−1.231	−0.569
	Sustained Willingness	Non-Self-Quantification Self-Quantification	2.956 3.733	0.624 0.669	−4.658	−1.112	−0.444
High Situational Involvement	Necessary Proportion	Non-Self-Quantification Self-Quantification	0.720 0.739	0.080 0.092	−0.851	−0.064	0.026
	Energy Consumption	Non-Self-Quantification Self-Quantification	279.500 272.167	45.964 40.379	0.657	−15.026	29.693
	Logarithm of Energy Consumption	Non-Self-Quantification Self-Quantification	5.619 5.596	0.173 0.148	0.560	−0.060	0.107
	Internal Motivation Arousal	Non-Self-Quantification Self-Quantification	3.644 3.700	0.631 0.818	−0.295	−0.433	0.322
	Sustained Willingness	Non-Self-Quantification Self-Quantification	3.844 3.789	0.531 0.776	0.324	−0.288	0.399

for details). Notably, under high situational involvement, consumers in the non-self-quantification condition showed some improvement in the proportion of necessary energy control activities and their sustained willingness. Hypothesis H3 was supported.

7. Discussions

7.1. Theoretical Contributions

This study, by focusing on the core concept of the sincerity of green behavior, provides a new perspective for evaluating consumer green behavior and understanding its sustainability. Traditional research has predominantly concentrated on the impact of individual traits and social norms on the outcomes of green behavior. For example, individual traits such as personal values and environmental attitudes promote green behavioral outcomes through self-determination mechanisms, while social norms may hinder or reinforce behavioral performance through group pressure pathways [55]. In contrast, this study innovatively introduces the contextual cue of self-quantification, exploring how it more fundamentally influences consumers’ internal motivation, the sincerity of green behavior, and consumers’ sustained willingness for such behavior under different situational conditions. This discovery not only enriches the theory of green behavior but also opens new directions for subsequent research.

Firstly, this study confirms that self-quantification, as an emerging technological tool, has differentiated impacts on green consumption activities with different goal orientations. Breaking through the limitations of past research that explored the positive utility of self-quantification from a single perspective of promoting goal orientation [26], as revealed by regulatory focus theory [56], promoting goal orientation corresponds to the pursuit of the “ideal self”, while defensive goal orientation corresponds to the avoidance of the “ought self”. This study examines the fundamental differences in the effects of self-quantification from the perspectives of these two types of goal orientations. In promoting goal-oriented green consumption activities, self-quantification may weaken consumers’ internal motivation and the sincerity of green behavior under low situational involvement, whereas this difference disappears under high situational involvement. Conversely, in defensive goal-oriented green consumption activities, self-quantification enhances consumers’ internal motivation and the sincerity of green behavior under low situational involvement. These findings reveal the complexity of the mechanisms through which self-quantification operates, emphasizing the importance of situational factors in green behavior research.

Secondly, by distinguishing between substantive and non-substantive environmental activities, as well as between necessary and unnecessary energy use activities, this study further refines the specific manifestations of green behavior. As emphasized by previous research, past pro-environmental behaviors (e.g., external feedback, self-quantification) encourage green behaviors in promotion-focused individuals but reduce them in prevention-focused individuals [57]. Past research has often used outcomes as the criteria for evaluating the effectiveness of green behavior [58]. Meanwhile, this refinement not only aids in a more precise understanding of the essence of green behavior but also provides new criteria for assessing the effectiveness of green behavior. As suggested by extremity standards theory [59], consumers’ differing perceptions of the “optimal solution” (e.g., maximum emission reduction) and “minimum requirements” (e.g., basic energy conservation) of behaviors affect their behavioral sincerity, which is as important as behavioral outcomes. This study highlights the sincerity of green behavior, rather than merely focusing on the outcomes, which is of significant importance for advancing in-depth research on green consumption behavior.

Lastly, the conclusions of this study shed light on potential misconceptions in the industry’s pursuit of green consumption outcomes. High levels of promoting goal-oriented green consumption outcomes and low levels of defensive goal-oriented green consumption outcomes do not equate to sincere greenness. This resonates with research on the moral licensing effect—when consumers gain “green credentials” through formalized behaviors, they may relax their requirements for substantive environmental protection, leading to a moral licensing trap [60]. This study confirms that truly sustainable green behavior should be from the heart, self-aware, and proactive—that is, sincere greenness. Compared to temporarily superior green behavior outcomes, consumers must sincerely engage in environmental conservation and energy saving, rather than merely going through the motions or becoming fatigued by compliance. Only such green behavior can be sustained in the long term. This perspective challenges the traditional outcome-oriented evaluation standards of green consumption, emphasizing the importance of internal motivation and sincerity in green behavior.

7.2. Managerial Implications

To promote goal-oriented green consumption activities, such as reducing carbon emissions or tree planting, companies should recognize that self-quantification may not always be effective when situational involvement is low. For instance, an environmental app that merely records users’ carbon emission reductions without offering opportunities for deep engagement and interaction may lead to a lack of genuine internal motivation and sincerity in green behavior among users. According to regulatory focus theory [56], promoting goal orientation requires a “gain frame”, and it is recommended to visualize long-term ecological benefits (e.g., tree growth trajectories) rather than short-term data rankings to avoid triggering formalized goal chasing. Therefore, companies can design more interactive and experiential environmental activities, such as organizing tree-planting events that encourage participants to plant trees themselves and use the app to track the growth process of the trees. This allows participants to experience a sense of achievement in environmental conservation, thereby enhancing the sincerity of their green behavior and their sustain willingness for it.

For defensive goal-oriented green consumption activities, such as controlling water and electricity usage, self-quantification can play a significant role when situational involvement is low. Based on extremity standards theory [59], it is essential to clearly define the “minimum compliance standards” for necessary energy use behaviors, such as community energy baseline values, and use quantified feedback to help consumers establish a defensive goal reference framework—that is, by intuitively displaying the “minimum compliance requirements” through quantified data, prompting consumers to adjust their behavior with the goal of avoiding exceeding standards. Companies should design user-friendly and real-time feedback tools to help consumers clearly understand their energy usage and guide them toward more energy-efficient behaviors. For example, a smart home system that monitors real-time water and electricity consumption can send alerts and suggestions to users via a mobile app, such as “Your water usage today is above average; please consider turning off unnecessary taps” or “Your appliance electricity consumption is high; we recommend switching to energy-efficient products”. Through such immediate feedback and personalized recommendations, consumers’ internal motivation to manage household energy use and the sincerity of their green behavior can be enhanced.

7.3. Research Limitations and Future Research Directions

The student demographic exhibits a high frequency of mobile application usage (e.g., the “Ant Forest” program) and familiarity with self-quantification tools, ensuring the smooth execution of experimental tasks (e.g., green energy value recording, energy consumption data feedback) and minimizing technical barriers’ interference with the results [21]. Jiangxi Province has actively promoted green urban development and low-carbon policies in recent years (e.g., the “Zero-Waste City” pilot program), making its residents’ awareness and participation in green consumption representative of typical characteristics in Chinese cities’ environmental practices [2]. However, university students’ green behaviors may be constrained by the specificities of campus life (e.g., collective dormitory energy usage). Future research could expand to include diverse age groups (e.g., working professionals) and household structures (e.g., households with children) to validate the generalizability of the findings. Subsequent studies should also conduct comparative experiments across multiple cities to examine the effects of regional economic levels and environmental policy intensity on self-quantification outcomes.

In addition to the type of activity under goal orientation and the degree of situational involvement, other factors may also moderate or interfere with the mechanism through which self-quantification influences the sincerity of consumers’ green behavior. The goal gradient behavior theory suggests that individuals’ goals can be categorized as either distant overall goals or proximal sub-goals. Moreover, the perceived proximity of proximal sub-goals is more likely to polarize individuals’ promoting and defensive behaviors compared to the perceived distance of distant overall goals. As the goal distance decreases, individuals’ efforts to approach promoting-oriented goals and avoid defensive-oriented goals will continuously increase [61]. In the context of consumers’ green consumption activities, there is always a certain time span between green behavior decisions and their outcomes, and the goals consumers face can vary between proximal sub-goals and distant overall goals. The distance of these goals across different time spans will influence the extent of consumers’ sincere efforts in green consumption activities [62]. Future research could further analyze whether the sincerity of consumers’ green behavior differs when facing goals with varying perceived distances in different goal-oriented green consumption contexts.

8. Conclusions

This study systematically analyzed and substantiated the process by which self-quantification differentially evokes consumers’ internal motivation under various situational conditions, thereby altering their behavioral sincerity and sustained willingness in green consumption activities. Through scenario-based simulation experiments, it was confirmed that in different goal-oriented green consumption activities, consumers indeed modified their underlying green behavioral sincerity and sustained willingness through self-quantification. The following was specifically shown.

On one hand, in the context of promoting goal-oriented green consumption activities, when the level of situational involvement is low, consumers who do not engage in self-quantification are more likely to participate in substantive environmental activities and less likely to participate in non-substantive environmental activities. These consumers exhibit strong internal motivation for green behavior, higher sincerity, and a strong sustained willingness for such behaviors. Conversely, consumers who engage in self-quantification participate less in substantive environmental activities and more in non-substantive ones, demonstrating weaker internal motivation, lower sincerity, and a reduced sustained willingness for such behaviors. However, when the level of situational involvement is high, both self-quantification and non-self-quantification consumers show similar tendencies when participating in substantive environmental activities, with no significant differences in the sincerity of green behavior or their sustained willingness.

On the other hand, in defensive goal-oriented green consumption activities, when the level of situational involvement is low, non-self-quantification consumers are less likely to engage in necessary energy use activities and more likely to participate in unnecessary energy use activities. These consumers exhibit weaker internal motivation for green behavior, lower sincerity, and a reduced sustained willingness for such behaviors. In contrast, self-quantification consumers are more likely to engage in necessary energy use activities and less likely to participate in unnecessary ones, demonstrating stronger internal motivation, higher sincerity, and a strong sustained willingness for such behaviors. When the level of situational involvement is high, both self-quantification and non-self-quantification consumers show similar tendencies when choosing necessary energy use activities and controlling unnecessary energy use behaviors, with no significant differences in the sincerity of green behavior or their sustained willingness.